Spectroscopy and Spectral Analysis, Volume. 42, Issue 9, 2757(2022)
Theoretical Study on Raman Characteristic Peaks of Coronavirus Spike Protein Based on Deep Learning
COVID-19, which has lasted for a year, has caused great damage to the global economy. In order to control COVID-19 effectively, rapid detection of COVID-19 (SARS-CoV-2) is an urgent problem. Spike protein is the detection point of Raman spectroscopy to detect SARS-CoV-2. The construction of spike protein Raman characteristic peaks plays an important role in the rapid detection of SARS-CoV-2 using Raman technology. In this paper, we used Deep Neural Networks to construct the amideⅠ and Ⅲ characteristic peak model of spike proteins based on simplified exciton model, and combined with the experimental structures of seven coronaviruses (HCoV-229E, HCoV-HKU1, HCoV-NL63, HCoV-OC43, MERS-CoV, SARS-CoV, SARS-CoV-2) spike proteins, analyzed the differences of amideⅠ andⅢ characteristic peaks of seven coronaviruses. The results showed that seven coronaviruses could be divided into four groups according to the amideⅠ and Ⅲ characteristic peaks of spike proteins: SARS-CoV-2, SARS-CoV, MERS-CoV form a group; HCoV-HKU1, HCoV-NL63 form a group; HCoV-229E and HCoV-OC43 form a group independently. The frequency of amideⅠ and Ⅲ in the same group is relatively close,and it is difficult to distinguish spike proteins by the frequency of amideⅠ and Ⅲ; the characteristic peaks of amideⅠ and Ⅲ in different groups are quite different, and spike proteins can be distinguished by Raman spectroscopy. The results provide a theoretical basis for the development of Raman spectroscopy for rapid detection of SARS-CoV-2.
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Shuang NI, Jia-xing WEN, Min-jie ZHOU, Jing-lin HUANG, Wei LE, Guo CHEN, Zhi-bing HE, Bo LI, Song-nan ZHAO, Zong-qing ZHAO, Kai DU. Theoretical Study on Raman Characteristic Peaks of Coronavirus Spike Protein Based on Deep Learning[J]. Spectroscopy and Spectral Analysis, 2022, 42(9): 2757
Category: Research Articles
Received: Mar. 5, 2021
Accepted: May. 26, 2021
Published Online: Nov. 17, 2022
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